Learn to create pie charts and bar charts within Jupyter notebooks using matplotlib and NumPy in this video tutorial by Charles Kelly. These are explained in the context of computer science and data science to technologists and students in preparation for
- [Narrator] The pie charts and bar charts file…in your exercise file folder…is prepopulated with import statements,…narrative text, links to source code for the examples,…and signatures for the pie function…and the bar chart function.…Before using this notebook,…select a cell that contains the import statement…and execute the cell by pressing Shift + Enter.…Next, go down through this snippet…and execute this cell.…If this pie chart is not displayed,…go to your toolbar,…and a window that indicates…an availability of a plot will be there.…
Click, and then your chart will be displayed.…Let's examine this code snippet…in the context of this plot.…The pie function has many parameters.…Fortunately, most of them are name parameters,…and have reasonable default values.…The first parameter, which is named x,…holds the dataset that will be displayed…within the pie chart.…The documentation for the plot tells us…that in addition to a basic example about a pie chart,…this example includes information about slice labels,…auto-labeling, offsetting a slice with an explosion,…
- Using Jupyter Notebook
- Creating NumPy arrays from Python structures
- Slicing arrays
- Using Boolean masking and broadcasting techniques
- Plotting in Jupyter notebooks
- Joining and splitting arrays
- Rearranging array elements
- Creating universal functions
- Finding patterns
- Building magic squares and magic cubes with NumPy and Python
Skill Level Intermediate
2. Create NumPy Arrays
3. Index, Slice, and Iterate
4. Plots: Matplotlib and Pyplot
5. Manipulate Arrays
6. Short Examples
7. Extended Examples
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